Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
whisper-finetuned-IEMOCAP – AI Model by VasilisAsim | AlphaNeural AI
You can deploy this model and start earning money today!
VasilisAsim
/
whisper-finetuned-IEMOCAP
like
0
transformers
safetensors
whisper
audio-classification
generated_from_trainer
BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised
finetune
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
whisper-finetuned-IEMOCAP
This model is a fine-tuned version of
BurningFang/finetuned_whisper_for_speech_emotion_recognition_optimised
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.6875
Accuracy: 0.5476
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 3e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
5.4490
1.0
402
1.3078
0.5146
4.1216
2.0
804
1.3081
0.5177
1.7227
3.0
1206
1.5997
0.5327
0.5641
4.0
1608
2.3515
0.5389
0.2490
5.0
2010
2.6875
0.5476
Framework versions
Transformers 5.9.0
Pytorch 2.11.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
